Thursday, November 19, 2015

Lesson 1,126½ in how to be a science disinformer, featuring Bob Tisdale

In this lesson about how to be a climate disinformer, I refer to a recent article by Bob Tisdale (archived here, cached here). In fact I refer to umpteen articles by Bob Tisdale, because his articles are often copies and pastes of his previous articles, with slight updates.

You can also watch a video with Tom Peterson, who gives The Story of Climate Data. This article is worth it for that alone. Dr Peterson is President of the World Meteorological Organization's Commission for Climatology, and recently retired from NOAA.

The purpose of the lesson, and hiding the closing of the gap

The purpose of the deception is to "prove" that all models are useless by hiding the closing of the gap.

Before you start, it's important to see what the observations actually show. Below is a chart of HadCRUT4, plotted with the multi-model mean of CMIP5. The 95% probability is for all uncertainties for HadCRUT observations - measurement and sampling, bias and coverage uncertainties. The uncertainties relating to the multi-model mean of CMIP5 are not plotted. As always, click on the chart to enlarge it.

As you can see, with 2015 year to date (to September 2015), the observations are now approaching the CMIP5 multi-model mean. This closing of the gap must be hidden from WUWT deniers at all costs. And it's not hard to do so if you follow the steps in the lesson.

Lesson 1,126½ in How to be a Science Disinformer

Now for Lesson 1,126½. This lesson is quite simple. Here are the five main steps.

Provide an introduction to tell the deniers what to think.

Rationalise your presentation of the data.

Make sure you don't include any error bars.

Use 61 month smoothing to ensure that the latest observations are discounted.

Add more words so that the chart illiterate know what to think.

Bob Tisdale has given us a live example. For Step 1, Bob told his readers what to think:

There are a number of ways to present how poorly climate models simulate global surface temperatures.

That's the first step. You want deniers to think that models are poor, so that's what you tell them.

For Step 2, Bob rationalised his presentation of the data this way (my emphasis):

Normally they are compared in a time-series graph. See the example in Figure 10. In that example, the UKMO HadCRUT4 land+ocean surface temperature reconstruction is compared to the multi-model mean of the climate models stored in the CMIP5 archive, which was used by the IPCC for their 5th Assessment Report. The reconstruction and model outputs have been smoothed with 61-month filters to reduce the monthly variations. Also, the anomalies for the reconstruction and model outputs have been referenced to the period of 1880 to 2013 so not to bias the results.

Now Bob didn't need to use 61 month smoothing to reduce the monthly variation. He could have shown the data as annual averages. By using 61 month smoothing - more than five years - he biases the chart away from the most recent 2½ years of observations. As Tamino once wrote:

More important, a moving average filter of width T will cut off a time span equal to half of T from both the beginning and the end of the time series — you lose what just might be the most interesting parts, the beginning and the end.

Bob Tisdale's T was 61 months, so by using this filter, he was able to chop off the "most interesting parts", in this case, 2½ years, which includes the recent uptick in surface temperature.

This can be illustrated in Bob's steps 3 and 4. Bob put up this chart (his Figure 10), which I've annotated:

In step 5, Bob again told his readers what to think, just in case they missed it. He wrote:

It’s very hard to overlook the fact that, over the past decade, climate models are simulating way too much warming and are diverging rapidly from reality.

Points to note - HadCRUT4 is reality

Now there are a couple of things to note before we go any further.

Bob endorses HadCRUT4. He calls it "reality". This is in contrast to most of the articles at WUWT, in which deniers more typically allege fraud and fudging of observations.

Bob claims the climate models are "diverging rapidly from reality". He can only make this statement because he's biased his chart away from the observations of the past 2½ years. In fact models and observations are converging, not diverging.

Illustrating the deception

Point 2 is demonstrated in the animation below, which goes from annualised data to data with a 61 month moving average:

The animation shows how using a 61 month moving average hides the fact that the gap is closing. It creates a false gap between the multi-model mean and observations. There is no reason to use a 61 month moving average. None at all, unless you want to deceive your readers, particularly the numerically-challenged.

Bonus lesson, the ½ - plot monthly differences (I'm not kidding!)

Now Bob gives his readers a bonus. He plots the monthly differences between CMIP5 and HadCRUT4. Monthly - I kid you not.

Models are not weather forecasts. If internal variability in a particular model run occurs at the same time as observations, that is purely coincidental. On top of that, using multi-model means for CMIP5 means that all the pluses and minuses of individual runs will be smoothed out. If you look at the annual charts above, you can immediately see the effect of smoothing. The CMIP5 plot is much smoother than HadCRUT4. If you were to look at an individual model run, it would have a lot more variability, just as observations have year to year variability.

Models are of climate - so they are intended to show longer term projections. By plotting monthly differences, Bob was able to amplify the differences to reach a maximum and minimum at times exceeding 0.4 °C. This isn't a great difference when it comes to monthly data. If he'd plotted the difference between an individual model run and HadCRUT4, he could have got an even greater difference.

Instead of plotting monthly differences like Bob did, how about decadal differences.

The blue bar is the difference. The white dotted line up top is the average actual year to date for this year (to September), from HadCRUT4.

As you can see, the biggest difference is the most recent decade, from 2006 to 2015 (with 2015 being average year to date to September). It is no secret that the most recent years have had temperatures in the lower end of those modeled. The difference for the decade to 2015 is 0.2 °C. Other than that, the largest difference in prior decades is 0.106 °C.

The reasons for the difference in recent years have been well-documented. The models include known forcings only to around 2005. After that, the forcings were estimates only. As it turned out:

The PDO index was negative from 2005, which suppressed surface temperatures. This internal variability is not programmed into the models, it is an emergent feature. Internal variability in the models is not expected to coincide with the timing in the real world. If it does happen to be timed with observations in any model run, it's pure coincidence. When you use multi-model means, this sort of variability will be averaged so you won't see the highs and lows of individual runs.

Volcanic forcing (which is negative) was greater than that applied to the CMIP5 models

Solar forcing (which is positive) was less than that applied to the models.

As you can see, Bob didn't need to go to such lengths. There was a difference between the modeled projections and observations. The reason he did can only have been to hide the fact that the gap is closing between the multi-model mean and observations.

If you're familiar with the "work" of Bob Tisdale, you'll know that he is not the least bit interested in exploring the reasons for any differences between modeled temperature and observations. That would conflict with his purpose in life. (His purpose being to deceive as many people as possible.)

Well that about covers it. This is the end of Lesson 1,126½ in how to be a climate science disinformer. Don't leave just yet, however, or you'll miss the bonus video below.

Bonus Video - Tom Peterson with The Story of Climate Data

If you are sceptical of all the false allegations made by deniers at WUWT, you will be even more so after watching this video. Anyone who's interested in the history and practice of preparing global surface temperature records should really enjoy this video. Tom Peterson talks about the early days of observing surface temperature, all the effort that has gone into constructing a global surface temperature record, the hoops that must be jumped through to obtain data from different countries, how gaps in the data are filled, how scientists have shown that poor siting makes little to no difference when it comes to broad-based surface temperature anomalies, and much more. (Don't mind the quality at the beginning - the video is well worth watching.)

The scientists who have worked so hard over the years to construct Bob's reality of surface temperature observations, should put disinformers like Anthony Watts and Bob Tisdale to shame.

From the WUWT comments

You can see how successful Lesson 1,126½ can be by reading the comments at WUWT. Bear in mind that I've only written about the part of Bob's article where he writes about climate models. Elsewhere in his article, he discusses the current El Niño.

Someone needs to tell highflight56433 that the record is adjusted to allow for UHI effects. Thing is, because they are adjusted, deniers cry foul.

November 16, 2015 at 7:07 pm
Should temperatures measured in UHI be reduced; after all they are an island? Where I live, driving into town always shows a +4 F to +9 F increase from the surrounding area which is primarily covered in trees rather than airport concrete and asphalt. Airport temps are only useful to aircraft performance.

markstoval wouldn't be interested in Tom Peterson's video or Bob Tisdale's reality of observations. He is a hard core denier/disinformer/defamer at WUWT.

November 17, 2015 at 2:09 am
But the objective of climate “science” is to show the greatest possible (or even impossible) temperature increase. They need to “adjust” those rural temps to match those city temps. Pronto!

MattN needs to wait a bit. Provided the lower troposphere calculations are reasonably accurate, he'll see his big spike early next year:

November 16, 2015 at 7:18 pm
Amazing. I distinctly remember that one of the reasons GISS had 2005 hotter than 1998 is they claimed GISS didn’t see all the heat the satellites did in 1998 and therefore had it cooler. Now the NINO3.4 temps are similar, they show a huge spike in temp. They really are having their cake and eating it too.

Eliza is very disappointed with Bob showing charts of temperature observations. She would much rather they remained hidden. She's also deluded for thinking that "warmists" would flog anything at WUWT, except in the negative sense, like here.

54 comments:

That stuff he is filtering out is not noise, it's signal. Recently I have been modeling QBO, and I find that the best correlation coefficient I get is with a 1 month smoother. That's all good information that one loses if filtering is applied with a heavy hand.

The internet needs to put a filter on Tisdale, or tell him to put a sock on it. That's an appropriate use of a a filter. He's creating as much spew as the local Koch refinery.

Thing is, because they are adjusted (data), deniers cry foul. They must get awfully upset at seasonally adjusted economic data such as the unemployment rate, the CPI, GDP, economic aggregates and annual accounts. Being a rational, consistent lot, no doubt they demand of their national statistics departments: "Call this an unemployment rate? What's with this seasonally adjusted stuff? Give us the raw data!" Hopefully, they'll never find out that economic statisticians sometimes make 'indirect adjustments' to economic data.

However, your comparison of Hadcrut and CMIP5 is not quite fair.In the spirit of Cowtan et al 2015 you should compare apples to apples as far as possible. You should use a Hadcrut mask on the models, with modelled SST and 2m air temp over land in the right places. If you did that, I'm sure that the average of the last 12 Hadcrut4 months would be quite close to the model mean. No gap anymore..

I have a related concern. HADCRUT4 does indeed have a baseline period of 1961 - 1990. But does the CMIP5 ensemble mean have the same baseline period? I think not. I believe it is 1986 - 2005.

According to what I've seen from Bob in the past, I doubt he is capable of adjusting either HADCRUT4 or the CMIP5 anomalies to have the same baseline. So I doubt the veracity of Bob's chart from the get-go, irrespective of the 61-month smoothing. But I didn't read his article, because... they are always tl;dr. So maybe I'm not giving him enough credit. By why, oh why, do deniers never include the baseline period in the text below their charts that show anomalies? :-\

I wanted to keep the article focused, but you raise an interesting point mm.

Bob did adjust the charts so they had the same baseline period. His baseline was the largest I've come across. It was 1880 to 2013 - goodness knows why. It doesn't make any difference to the trend of course. An odd choice, just the same.

Contrast that extended baseline period (and his choice of 61 months for a moving average) with his decision to plot the *monthly* difference between modeled and observed data.

I'll add that in the past Bob's aligned data to a single data point. That is, he just picked the start date and made all his plots start on the same temperature for that date - no alignment to a baseline.

He finally got the message that that's a no-no. At least I think he did. I haven't noticed him doing that lately. (Could've been he read it here.)

Of course, Sou, right after I posted I noticed the '(Reference: 1880 to 2013)' in Bob's chart. So I'll have to assume he adjusted both the HADCRUT4 and CMIP5 anomalies correctly. Maybe you could check his work?

And... I'm also assuming you adjusted the CMIP5 anomalies to the HADCRUT4 baseline? :-)

Thanks for the compliments Sou,The lessons from Cowtan et al 2015 are really inconvenient in Deniersville. They are dead silent about it..Regarding length of the baseline, I recommend 60 years (1951-2010 used in my chart above), since I believe in natural 60-year cycles. Using the GISS standard baseline 1951-1980, which is a cold period, would give observations a lift versus models. A cheap trick for the alarmist but unfair. 1961-1990 is relatively balanced, whereas 1981-2010 is relatively hot and a disadvantage for observations.Spencer& Christy commonly use 1979-1983 for base-lining models and observations, a period which includes one of the two strongest el Ninos of the 20th century. Say no more..

I don't know about any 60 year cycles. The period Bob Tisdale shows gives a slightly higher baseline than HadCRUT's 1961-90. I think 30 years is usually considered long enough, unless you want to measure deviation from a particular period (eg twentieth century).

Spencer and Christy's five year baseline was chosen to deceive. It's too short for comparisons between data sets.

Comparing apples to apples is a schoolboy error in my opinion, they are the same as your article demonstrates. Climate models == Earth's temperature, BORING. What Bob should do is compare CMIP5 to the working hours of a strawberry using the wave equation of the level 4 multiverse. Imagine the article that would produce.

Tizzy has spent a lot of time pooh-poohing the observations that suggest this EL Nino is a biggie. By next autumn, with the global mean T responding to current high indices, and his untenable model/data 'mismatch' fiddle overexposed, Tizzy will have retired again.

Question. Who is the most highly-regarded and well-credentialed AGW skeptic? The one that is most intimidating to other climate scientists? Would you agree that it is Richard Lindzen? I don't think it is Curry or Spencer.

In contrast, I bet most climate scientists treat Tisdale with as much respect as something they find sticking to the bottom of their shoe.

Publications wouldn't matter if Bob was reporting science. Since he's disputing science, if he wanted to impress beyond cranks like Judith Curry and Anthony Watts, he'd have to write up and get published some solid evidence to support his argument that it's El Ninos causing global warming not CO2. He doesn't have the evidence, the maths, the statistics, the research skills or the general know-how to try. And he doesn't have the physics or chemistry to argue that greenhouse gases aren't (greenhouse gases).

I don't agree with bob tisdale usually, but here I have to say a 61 month smoothing is better as it will smooth out ENSO. ENSO is already effectively smoothed out in the model mean, so to compare like with like the observations should be smoothed too.

Or to put it another way, if observations track the model mean then they should be sometimes higher than it and sometimes lower, in roughly equal measure. Given we are in a strong el nino we should be much higher than it - if not then when would be expected to be? So to be merely approaching the model mean is more an indication that the longterm observations are tracking below the model mean.

Really this is because the model mean increases since 1980 at about 0.2C/decade while surface temperatures are more like 0.15C/decade. Divergence is inevitable and it has become more obvious to the eye. Whether statistically significant or not.

Ultimately temperatures have to do a little more than they've done already during this recent El Nino in order for the observations to reach the model mean. A shortfall of 0.05C/decade will just lead to divergence and in 10 years time even a 12 month smoothed graph during the peak of super el nino will fall short of the model mean.

You don't smooth out the effects of ENSO! You incorporate it in to the model. That's what Rahmstrff and Foster do, and lots of other smart (i.e. non-Tisdale) scientists do. I do it with my CSALT model (google CSALT and ENSO)

First of all, Bob said he was using 61 month smoothing to "to reduce the monthly variations", not to smooth out ENSO.

Secondly, if he just wanted to smooth out ENSO, why would he also smooth the CMIP5 multi-model mean? That's already "smoothed" out ENSO by averaging all the model runs. (ENSO events where they occur would be timed differently in the different model runs. Using a mean averages the pluses and minuses of variability like ENSO events.)

Thirdly, if he wanted to get rid of ENSO he'd subtract it, not use a moving average.

If the models were populated with the observed forcings (replacing the estimates since 2005 for example), then I'd expect them to be closer to observations. As I intimated in the article, if the PDO has shifted to a warm phase, then it may not be too long before observations catch up.

A few things will be needed - the models to be populated with more accurate forcings (ie allowing for observed volcanic aerosols and slightly lower TSI), improved observations, particularly of the polar regions were observations are sparse, internal variability which has tended to make the surface warm more slowly, to shift to faster warming.

As for your "model mean" comments, have you thought them through? You are falling for what is essentially a version of the Gambler's Fallacy.

The ensemble mean is just that and is as highly improbable as seeing head-tail-head-tail...etc. in coin flips. Individual model runs reflect actual possibilities. And the actual Earth ALWAYS reflects only a single model run, not the ensemble mean.

If you should happen to flip 5 tails in a row, do you suddenly "expect" the proportion of heads to tails in the entire series counting those 5 tails to rise above 50%? I should hope not. After observing 5 tails in a row, the expectation of even seeing 50% heads in the entire series is forever less than 50% only asymptoting to 50% at infinity.

I am pretty sure the actual Earth reflects exactly NONE of the model runs and will not unless we run an infinite number of them with every imaginable variable. I mean, how many of the models include asteroid strikes? Ice-9 release? Nuclear war? and other such unpredictable events. The ensemble mean is not the most likely scenario but, as the name says, the mean of all the runs.

Poorly stated on my part. The Earth is the equivalent of a single model run. And as such no more likely to follow the ensemble mean than any individual model run even if all assumptions are perfectly correct.

SInce we're on the topic of abuse of temperature data "Steven Goddard" has produced a seriously unhinged screed on why the record-breaking Giss data for Oct 2015, posted on 17th Oct, are "fraudulent". He says their data set is far from complete, missing out large chunks of data. The "evidence": an incomplete anomaly map posted, not by GISS but ....... by NOAA on its website on 17th. He's either even more stupid then previously thought or his dishonesty has reached new levels of blatantness (if I'm allowed to use that word). Goddard's post is doing the rounds of denier blogs: e.g. cross posted at Tallbloke's blog:

Just to clarify: the NOAA map was posted 2 days before NOAA released its October data set. That was why the map was incomplete: NOAA were still finalising data to add to the map. Steve either failed to realise this or fails to point the fact to his followers

Really off topic ... but did realclimate.org close down ... or did they forget to renew their domain name??? If the later let's hope they solve that before WUWT grabs it!! Maybe SOu has the wherewithall to know what it's all about? Or, am I being spoofed?

For a long time now I have been getting periodic and frequent 503 errors. This indicates a problem with the backend handling the number of page requests. My best guess is that they are under a continuous and low level DOS attack.

And given the sort of whack jobs on the denial side, it wouldn't surprise me.

No there is for sure something up with realclimate.orgI get a holding page and a message that the domain has expired. From the whois data it looks like they let it lapse on the 19th and though renewed (by Betsy Ensley of Environmental Media Services) it is still directing to a placeholder page.

"My best guess is that they are under a continuous and low level DOS attack."

I have been thinking along those lines as I had been having similar trouble during the course of this week. And expecting a ramp up in dirty tricks from the fossil fuel FUD aiders and abettors I would not be surprised.

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All you need to know about WUWT

WUWT insider Willis Eschenbach tells you all you need to know about Anthony Watts and his blog, WattsUpWithThat (WUWT). As part of his scathing commentary, Wondering Willis accuses Anthony Watts of being clueless about the blog articles he posts. To paraphrase:

Even if Anthony had a year to analyze and dissect each piece...(he couldn't tell if it would)... stand the harsh light of public exposure.

Definition of Denier (Oxford): A person who denies something, especially someone who refuses to admit the truth of a concept or proposition that is supported by the majority of scientific or historical evidence.
‘a prominent denier of global warming’
‘a climate change denier’

Alternative definition: A former French coin, equal to one twelfth of a Sou, which was withdrawn in the 19th century. Oxford. (The denier has since resurfaced with reduced value.)